Related Experiment Video
Updated: Jun 3, 2026

Assessing the Coherence of Parents' Short Narratives Regarding their Child Using the Five-Minute Speech Sample Procedure
Published on: September 19, 2019
A multivariate model of parent-adolescent relationship variables in early adolescence
Cliff McKinney1, Kimberly Renk
1Department of Psychology, Mississippi State University, USA. cmckinney@psychology.msstate.edu
Abstract:
Given the importance of predicting outcomes for early adolescents, this study examines a multivariate model of parent-adolescent relationship variables, including parenting, family environment, and conflict. Participants, who completed measures assessing these variables, included 710 culturally diverse 11-14-year-olds who were attending a middle school in a Southeastern state. The parents of a subset of these adolescents (i.e., 487 mother-father pairs) participated in this study as well. Correlational analyses indicate that authoritative and authoritarian parenting, family cohesion and adaptability, and conflict are significant predictors of early adolescents' internalizing and externalizing problems. Structural equation modeling analyses indicate that fathers' parenting may not predict directly externalizing problems in male and female adolescents but instead may act through conflict. More direct relationships exist when examining mothers' parenting. The impact of parenting, family environment, and conflict on early adolescents' internalizing and externalizing problems and the importance of both gender and cross-informant ratings are emphasized.
Related Concept Videos
Influence of Parents and Peers on Identity
Parental Influence on Identity Development
Parents serve as primary guides and managers in an adolescent's life, offering support instrumental in decision-making and personal growth. This guiding role...
Cognitive Development During Adolescence
Relationship with Parents: Attachment
Erikson's Theory on Socioemotional Development during Adolescence
Sources of Self-Esteem I: Family Experience
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...

